{"id":"W4408337152","doi":"10.1002/smtd.202401587","title":"Double‐Angling‐Subspace Enabled Laser‐Induced Fluorescence Method for Determining the Types and Mass Ratio of Marine Microplastics","year":2025,"lang":"en","type":"article","venue":"Small Methods","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China; Natural Science Foundation of Shandong Province; Texas Space Grant Consortium","keywords":"Microplastics; Linear subspace; Subspace topology; Fluorescence; Biological system; Computer science; Environmental science; Chemistry; Mathematics; Environmental chemistry; Artificial intelligence; Biology; Physics; Optics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004128038,0.000603865,0.000343238,0.0009864095,0.0003531666,0.0004271017,0.0003626454,0.0004014106,0.001183094],"category_scores_gemma":[0.0006535801,0.0002480285,0.0003483403,0.0008328962,0.0004676509,0.0009924992,0.0007303669,0.0006042038,0.0005814607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002888211,"about_ca_system_score_gemma":0.0005217845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007859415,"about_ca_topic_score_gemma":0.001805723,"domain_scores_codex":[0.9995613,0.00007480728,0.00001758008,0.0001281405,0.0001698617,0.00004820419],"domain_scores_gemma":[0.9996081,0.0001014371,0.00008620651,0.00005218617,0.0001205102,0.00003169704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001844089,0.00008552927,0.003781016,0.000228733,0.0000327013,0.0001015019,0.0001698676,0.007437126,0.8284977,0.002958345,0.0006233074,0.1558998],"study_design_scores_gemma":[0.00001633029,0.0002561908,0.005970185,0.00002062691,0.00002977694,0.000462751,0.0001759941,0.1734797,0.8106566,0.002422068,0.006371371,0.0001384255],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2096792,0.0009986141,0.7834099,0.0001368141,0.00006775037,0.00009942045,0.0004177438,0.001147356,0.004043311],"genre_scores_gemma":[0.5151175,0.00096036,0.4807166,0.00009582796,0.00003124339,0.0001561039,0.0004045577,0.0001022951,0.002415372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001183094,"threshold_uncertainty_score":0.003957868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02608419035164243,"score_gpt":0.3130354291292908,"score_spread":0.2869512387776484,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}